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Due to the significant effect of abnormal arrivals on localization accuracy, a novel acoustic emission (AE) source localization method using clustering detection to eliminate abnormal arrivals is proposed in the paper. Firstly, iterative weight estimation is utilized to obtain accurate equation residuals. Secondly, according to the distribution of equation residuals, clustering detection is used to identify and exclude abnormal arrivals. Thirdly, the AE source coordinate is recalculated with remaining normal arrivals. Experimental results of pencil-lead breaks indicate that the proposed method can achieve a better localization result with and without abnormal arrivals. The results of simulation tests further demonstrate that the proposed method possesses higher localization accuracy and robustness under different anomaly ratios and scales; even with abnormal arrivals as high as 30%, the proposed localization method still holds a correct detection rate of 91.85%.

Earthquake is one of the most damaging disasters in Bangladesh and vulnerability assessment is the precondition for evaluating the risk of earthquake. Therefore, the main goal of this study is to estimate the vulnerability in Chittagong city by using analytical hierarchy process. Several factors have been applied to generate social vulnerability and structural vulnerability. The analytical hierarchy process has been applied for criteria weight estimation, ranking of priorities and to evaluate the alternatives of criterion. A pair-wise comparison is applied at all levels. Finally, the vulnerable zones of Chittagong city have been extracted. The findings through this research reveal that Chittagong city exhibits both social and structural vulnerabilities. In terms of social vulnerability, 21.74% of Chittagong city falls under very high, 33.60% high, 10.27% moderate, 7.78% low and 26.6% is under very low vulnerability areas and due to the structural vulnerability, 21.75% of the city area is under very high, 29.67% high, 15.90% moderate, 30.80% low and 1.87% is under very low vulnerability zone. The present study of earthquake vulnerability assessment may be fruitful in combating the losses and mitigating the risk.

Background In children, the use of actual weight or predicted weight from various estimation methods is essential to reduce harm associated with dosing errors. This study aimed to validate the new locally derived Lusaka formula on an independent cohort of children undergoing surgery at the University Teaching Hospital in Lusaka, Zambia, to compare the Lusaka formula's performance to commonly used weight prediction tools and to assess the nutritional status of this population. Methods The Lusaka formula (weight = [age in months/2] + 3.5 if under 1 year; weight = 2×[age in years] + 7 if older than 1 year) was derived from a previously published data set. We aimed to validate this formula in a new data set. Weights, heights, and ages of 330 children up to 14 years were measured before surgery. Accuracy was examined by comparing the (1) mean percentage error and (2) the percentage of actual weights that fell between 10% and 20% of the estimated weight for the Lusaka formula, and for other existing tools. World Health Organization (WHO) growth charts, mid upper arm circumference (MUAC), and body mass index (BMI) were used to assess nutritional status. Results The Lusaka formula had similar precision to the Broselow tape: 160 (48.5%) vs 158 (51.6%) children were within 10% of the estimated weight, 241 (73.0%) vs 245 (79.5%) children were within 20% of the estimated weight. The Lusaka formula slightly underestimated weight (mean bias, -0.5 kg) in contrast to all other predictive tools, which overestimated on average. Twenty-two percent of children had moderate or severe chronic malnutrition (stunting) and 4.7% of children had moderate or severe acute malnutrition (wasting). Conclusions The Lusaka formula is comparable to, or better than, other age-based weight prediction tools in children presenting for surgery at the University Teaching Hospital in Lusaka, Zambia, and has the advantage that it covers a wider age range than tools with comparable accuracy. In this population, commonly used aged-based prediction tools significantly overestimate weights.

Introduction: Weight estimation in children is critical in paediatric emergencies. The Broselow Tape (BT) and most age-based formulae for weight estimation were derived in high-income countries and are thought to overestimate the weight of children in low-income countries. This study sought to validate the 2017 BT, and eight age-based weight estimation formulae among Ghanaian children and to derive a weight estimation formula using this data. Methods: A cross-sectional study was conducted in the Tamale Teaching Hospital (TTH) in Ghana. Children aged between 2 months and 13 years had their weights estimated by the 2017 BT and eight age-based formulae. These estimated weights were compared to the weight of the children measured by a calibrated Seca scale using mean percentage error (MPE) and the percentage of weight estimates within 10% and 20% of actual weight. Bland-Altman method was used to assess agreement between estimated and actual weight of the children. A new formula was derived by linear regression. Results: Seven hundred and seventy-five children took part in the study. The 2017 BT, Original APLS (APLS1) and Nelson's formulae performed best with proportion of weight estimates within 10% of actual weight being 47.5%, 51.1% and 47.5% respectively. The formula developed in this study was: WE = 3Am / 10 + 5 (for infants

OBJECTIVE The aim of this study was to determine accuracy of height and weight prediction by a 3-dimensional (3D) camera. METHODS A total of 453 patients whose computed tomography imaging used a 3D camera from December 19, 2018 to March 19, 2019 were retrospectively identified. An image of each patient was taken before the computed tomography by a 3D camera mounted to the ceiling. Using infrared imaging and machine learning algorithms, patient height and weight were estimated from this 3D camera image. A total of 363 images were used for training. The test set consisted of 90 images. The height and weight estimates were compared with true height and weight to determine absolute and percent error. A value of P < 0.05 indicated statistical significance. RESULTS There was 2.0% (SD, 1.4) error in height estimation by the 3D camera, corresponding to 3.35 cm (SD, 2.39) absolute deviation (P = 1, n = 86). Weight estimation error was 5.1% (SD, 4.3), corresponding to 3.99 kg (SD, 3.11) absolute error (P = 0.74, n = 90). CONCLUSION Pictures obtained from a 3D camera can accurately predict patient height and weight.

Background Accurate estimation of food portion sizes remains an important challenge in dietary data collection. The present study aimed to develop a food atlas with adequate visual reference to improve the accuracy of dietary surveys in China. Methods A food atlas for dietary surveys in China was developed using three visual reference systems, namely, regularly placed food portions, the two‐dimensional background coordinates and common objects known in daily life. The atlas was validated by estimating a meal before and after using the food atlas, and differences in weight estimation were compared using a paired t‐test. In total, 50 college students participated in the study. Results After determination of food varieties; design of the food display; purchase, processing, cooking and weighing of food; photographing food; post‐image processing and data processing, a total of 799 pictures of 303 types of food and two types of tableware were produced. The mean value of food weight estimated with the atlas was closer to the actual weight, and the variation range of these values was smaller and more stable than that estimated without the atlas. The differences estimated before and after using the atlas for all foods were significant (P, Accurate estimation of food portion sizes remains an important challenge in dietary data collection. We developed a food atlas for retrospective dietary surveys in China, which can be used to enable a better understanding of nutritional adequacy in the Chinese population.

In the past few decades, both academicians and industries have shown interest toward the agricultural post-harvest operation aiming to reduce the post-harvest losses. In order to assist farmers in ...

OBJECTIVE To develop and validate a weight estimation tool applicable in paediatric emergency care. METHODS Using anthropometric data from a computerized database of the primary health care paediatric services, Bilbao (Basque Country, Spain), linear regression models were developed with the objective of estimating weight from height. Subsequently, these models were prospectively validated using a consecutive sample of children attended in the emergency department of two tertiary hospitals. Estimated weights were compared with actual weights, calculating the intraclass correlation coefficient (ICC), mean difference and percentages of estimations falling within 10% and 20% of the actual weight. RESULTS Using anthropometric data from 15522 children two weight predictive formulas were developed (Bilbao Formulas). The formulas were validated on a sample of 780 children and estimated weight values with a high degree of intraclass correlation with the real weight (ICC=.93, P

Background: In emergencies, two commonly used weight estimation methods are Nelson and mid-arm circumference (MAC)-based formulae. Nelson's method requires the child's age while the MAC formula offers weight estimation without any prior details of the child, which is useful in our environment due to the lack of proper vital statistics documentation. Methodology: We measured the weight, height, and MAC of 1390 children aged 1–12 years. Values got from the measurements were substituted in MAC and Nelson formulae for weight estimation. The estimated weights were compared to the actual weights of the children. Results: A total of 1390 children were enrolled. The mean of enrolled children's actual weight was significantly higher than the mean weight estimated using MAC and Nelson formula. MAC method overestimated weight in children 1–7 years and underestimated weight in those 8–12 years old. On the other hand, the Nelson formula underestimated weights in children 2–11 years and overestimated weight in 1 and 12-year olds. Conclusions: Both the MAC and Nelson method have their deficiencies in weight estimation. Though the Nelson formula appears slightly more accurate than the MAC, weight estimates from both methods were mostly within the actual weight agreement limits.

This study was conducted to estimate the body weight of Korean cattle (Hanwoo) using three-dimensional image. A time-of-flight camera and a stereo vision camera were used to acquire top-view images for Hanwoo. Multiple linear regression model incorporating body dimensions and age was developed to estimate the body weight. The prediction models with or without age variable were determined. Incorporating age variable that correlates with body weight improved the coefficient of determination for both TOF images and stereo vision images. The weight estimation error was greatly reduced under the condition that calves less than 6 months old were excluded. It was concluded that 3-D image is a promising technique for estimating the body weight of Hanwoo cattle.

Objective The primary aim of this study was to prospectively compare the performance of the Broselow tape, Mercy method, pediatric advanced weight prediction in the emergency room extra-long (PAWPER XL) tape, and PAWPER XL mid-arm circumference (MAC) method in estimating the weight of children from a low-income setting. The secondary aim was to analyze the time taken to perform each method. Methods This analyzed a convenience study sample of 300 children aged 0 to 18 years at the Baragwanath Hospital in South Africa. Weight estimations were obtained using each of the weight estimation systems on each child. These weight estimations were then compared against the actual weight to determine bias, precision, and accuracy of the estimation methods. Results The PAWPER XL tape and PAWPER XL-MAC methods performed the best and provided estimated weights within 10% of the actual weight in 62.7% and 67.3% of cases, respectively, followed by the Mercy method (56.5%) and Broselow tape (43.9%). The use of MAC improved the accuracy of estimation, especially in heavier and taller children. The median times taken to perform measurements using the Broselow tape, Mercy method, PAWPER XL tape, and PAWPER XL-MAC method were 11.3 seconds, 34.7 seconds, 9.3 seconds, and 33.9 seconds respectively. Conclusion The PAWPER XL tape and PAWPER XL-MAC methods were the most accurate methods of estimating weight in this group of children. These methods may be considered in preference to the Broselow tape or the Mercy method for emergency weight estimation in low socioeconomic status populations.

Objectives In obese children, when drug therapy is required during emergency care, an estimation of ideal body weight is required for certain drug dose calculations. Some experts have previously speculated that age‐based weight estimation formulas could be used to predict ideal body weight. The objectives of this study were to evaluate how accurately age‐based formulas could predict ideal body weight and total body weight in obese children. Methods Three age‐based weight estimation formulas were evaluated in a secondary analysis, using a pooled sample of children from 3 academic emergency departments in South Africa. The estimates produced by the 3 formulas (and the PAWPER XL tape as a control) were compared against measured total body weight and ideal body weight. The percentages of estimates falling within 10% of the standard weight were used as the primary outcome measure (PW10). Results This study included 1026 children. For ideal body weight estimations in obese children, the old Advanced Life Support formula, the new Advanced Life Support formula, and the Best Guess formula achieved PW10s (with 95% confidence intervals [CIs]) of 29% (27.2%, 30.8%), 41.4% (38.9%, 43.9%), and 48.3% (45.3%, 51.3%), respectively. For total body weight estimations, the formulas achieved PW10s of 3.6% (3.4%, 3.8%), 5.2% (4.9%, 5.5%), and 19.0% (17.8%, 20.2%). The PAWPER XL tape achieved an accuracy of ideal body weight estimation of 100% (93.9%, 100%) and total body weight estimation of 49.7% (46.7%, 52.7%) in obese children. Conclusions The age‐based formulas were substantially less accurate at estimating total body weight and ideal body weight than existing length‐based methods such as the PAWPER XL tape, and should not be used for this purpose.

IntroductionWeight estimation of both adult and paediatric patients is often necessary in emergency or low-resource settings when it is not possible to weigh the patient. There are many methods for paediatric weight estimation, but no standard methods for adults. PAWPER and Mercy tapes are used in children, but have not been assessed in adults. The primary aim of this study was to assess weight estimation methods in patients of all ages.MethodsPatients were prospectively recruited from emergency and outpatient departments in Kigali, Rwanda. Participants (or guardians) were asked to estimate weight. Investigators collected weight, height, mid-arm circumference (MAC) and humeral-length data. In all participants, estimates of weight were calculated from height and MAC (PAWPER methods), MAC and humeral length (Mercy method). In children, Broselow measurements and age-based formulae were also used. The primary outcome measure was the proportion of estimates within 20% of actual weight (p20).ResultsWe recruited 947 participants: 307 children, 309 adolescents and 331 adults. For p20, the best methods were: in children, guardian estimate (90.2%) and PAWPER XL-MAC (89.3%); in adolescents, PAWPER XL-MAC (91.3%) and guardian estimate (90.9%); in adults, participant estimate (98.5%) and PAWPER XL-MAC (83.7%). In all age groups, there was a trend of decreasing weight estimation with increasing actual weight.ConclusionThis prospective study of weight estimation methods across all age groups is the first adult study of PAWPER and Mercy methods. In children, age-based rules performed poorly. In patients of all ages, the PAWPER XL-MAC and guardian/participant estimates of weight were the most reliable and we would recommend their use in this setting.

OBJECTIVES The aims of this study were to determine and improve accuracy of the Broselow Tape (BT) in estimating children's weight by adding body habitus parameters. METHODS This cross-sectional study was conducted in an urban hospital pediatric clinic. Children up to 8 years old coming in for well-child visit were included. Children with acute illness or presence of any chronic condition potentially resulting in growth disturbance and out of BT height range were excluded. The following body habitus parameters were measured using the Centers for Disease Control and Prevention guidelines: actual weight, predicted weight using BT (BTW), mid-thigh circumference (MTC), body mass index, mid-arm circumference, and waist-to-hip ratio. RESULTS A total of 301 children were enrolled. Of these, 151 were male (50%). Hispanics constituted 160 (53.2%). There was a positive linear association between BTW and actual weight in the overall cohort (adjusted R = 0.9164, P < 0.001). However, there was a difference in this association among children younger than 2 years and children older than 2 years (adjusted R = 0.89 vs 0.4841). Incorporating MTC and/or waist circumference along with BTW in the model increased the accuracy, providing a better estimate of actual weight (adjusted R = 0.94, P < 0.001). CONCLUSIONS We conclude that there might be inaccuracies in the weight predicted by BT in our patient population, especially those weighing more than 15 kg and older than 2 years. Our study also demonstrates that MTC correlates closely with the actual weight and could be used in addition to BT for more accurate weight estimation.

Introduction: Accurate fetal weight assessment is a problem which is associated where resources are subject to availability. Both low and high birth weight is connected with augmented prospect of complications of new born during labour and purperium. Fetal weight assessment can reduce the risk of complications that are challenging in maternal and neonatal of Symphysio-fundal height measurement by adopting Johnson’s Formula. For the fetal weight estimation a method that has now come to be prevalent. By adopting Johnson’s formula along with its comparison to the actual birth weight. The present study thus aimed to determine fetal weight accuracy. Materials and Methods: Present study of prospective analytical was accepted to in the Obstetrics and Gynaecology Department of a tertiary care hospital in Pune. Study included a total of 500 pregnant women attending the OPD with full term pregnancy till onset of labour, fulfilling the inclusion criteria. Adopting Johnson’s formula birth weight estimation has been done along with the results were correlated with definite birth weight. Using SPSS ver. 21.0 the analysis of Data had been performed. Results: As per the prediction of Mean birth weight by clinical (Johnson’s formulae) and actual birth weight was 3.13 Kg and 2.89 Kg correspondingly. Johnson’s formulae’s co-relates well with actual birth weight (r-0.86; 95% CI: 0.84-0.88), though prediction of fetal weight was slightly on a higher side. In 60.8% cases the difference was within range of 10% and in 84.8% the difference was less than 15%. The mean difference in estimation was highest in babies those are in low birth weight i.e. Conclusion: Our observation indicates that as a diagnostic tool there is visibly a role for clinical birthweight estimation, in a pregnancy term suggesting that, to manage labour as well as delivery clinical estimation is sufficient. Keywords: Birth weight, Birth weight estimation, Johnson’s formulae, Symphysio-fundal height.

With the advancement in autonomic computing technology, quality assurance for autonomic software is another big challenge to be faced by IT industries. Autonomic software is quite different in work...

According to the Food and Agriculture Organization, the world production of date fruits is 8,526,218 tons and around 1,302,859 tons in the Kingdom of Saudi Arabia (KSA) in 2018. There are several types of date fruits, and the most common in KSA are Barhi, Khalas, Meneifi, Naboot Saif, and Sullaj. Moreover, there are around five main maturity levels: Immature, Khalal, Khalal with Rutab, Pre-Tamar, and Tamar. Harvesting date fruits is performed according to its maturity level and type, which is a critical decision that significantly affects profit. In this paper, we propose a smart harvesting decision system to estimate date fruits type, maturity level, and weight using computer vision (CV) and deep learning (DL) techniques. The proposed system consists of three sub-systems: Dates maturity estimation system (DMES), type estimation system (DTES), and dates weight estimation system (DWES). We utilized four DL architectures, including ResNet, VGG-19, Inception-V3, and NASNet for both DMES and DTES and support vector machine (SVM) (regression and linear) for DWES. We evaluated the performance of the proposed system using the dataset collected by the Center of Smart Robotics Research. Using multiple performance metrics, DTES achieved maximum performance of 99.175% accuracy, an F1 score of 99.225%, 99.8% average precision, and 99.05% average recall. The maximum performance of DMES was 99.058% accuracy, F1 score of 99.34%, 99.64% average precision, and 99.08% average Recall. DWES achieved a maximum performance of 84.27% using SVM-Linear.

Background Accurate flap weight estimation is crucial for preoperative planning in microsurgical breast reconstruction; however, current flap weight estimation methods are time consuming. It was our objective to develop a parsimonious and accurate formula for the estimation of abdominal-based free flap weight. Methods Patients who underwent hemi-abdominal-based free tissue transfer for breast reconstruction at a single institution were retrospectively reviewed. Subcutaneous tissue thicknesses were measured on axial computed tomography angiograms at several predetermined points. Multivariable linear regression was used to generate the parsimonious flap weight estimation model. Split-sample validation was used to for internal validation. Results A total of 132 patients (196 flaps) were analyzed, with a mean body mass index of 31.2 ± 4.0 kg/m2 (range: 22.6–40.7). The mean intraoperative flap weight was 990 ± 344 g (range: 368–2,808). The full predictive model (R 2 = 0.68) estimated flap weight using the Eq. 91.3x + 36.4y + 6.2z – 1030.0, where x is subcutaneous tissue thickness (cm) 5 cm lateral to midline at the level of the anterior superior iliac spine (ASIS), y is distance (cm) between the skin overlying each ASIS, and z is patient weight (kg). Two-thirds split-sample validation was performed using 131 flaps to build a model and the remaining 65 flaps for validation. Upon validation, we observed a median percent error of 10.2% (interquartile range [IQR]: 4.5–18.5) and a median absolute error of 108.6 g (IQR: 45.9–170.7). Conclusion We developed and internally validated a simple and accurate formula for the preoperative estimation of hemi-abdominal-based free flap weight for breast reconstruction.

BackgroundErroneous weight estimation during the management of emergency presentations in adults may contribute to patient harm and poor outcomes. Patients can often not be weighed during emergencies and a weight estimation is required to facilitate weight-based therapies. Many existing methods of weight estimation are either unacceptably inaccurate or very difficult to use during the provision of emergency care.MethodsThe weight estimation system developed in this study was based on and modified from the PAWPER XL-MAC method, a paediatric weight estimation system that uses recumbent length and mid-arm circumference (MAC) to predict total body weight. This model was validated in the 2015 – 2018 National Health and Nutrition Examination Survey (NHANES) datasets. The primary outcome measure was to achieve >95% of estimations within 20% of measured weight (P20>95%).ResultsThe modified PAWPER XL-MAC model achieved a P20 of 96.0% and a P10 of 71.3% in the validation dataset (N=11520). This accuracy (P20>95%) was maintained in both sexes, all ages, all ethnic groups, all lengths and in all habitus-types, except for the subgroup of severely obese individuals.ConclusionsThe modified PAWPER XL-MAC model proved to be a very accurate method of weight estimation. It is more accurate than most other published reports of existing methods of weight estimation, except for patients’ own estimations. It therefore could have a role in facilitating emergency drug dose calculations, if prospective studies bear out the accuracy found in this study.

Objective Many emergency drug and fluid doses are weight dependent in adults, but in resuscitation and low‐resource settings it can be impractical or impossible to weigh a patient. It is especially important to obtain accurate weight estimation for dose calculations for emergency drugs with narrow therapeutic ranges. Several weight estimation methods have been proposed for use in adults, but none is widely established. The aim of this study was to compare the accuracy of adult weight estimation methods. Methods Demographic and body measurement data were obtained from the US National Health and Nutrition Examination Survey (NHANES), and 7 previously published weight estimation methods were used to estimate the weight for each individual. The primary outcomes were the proportions of estimates within 10% and 20% of actual weight (P10, P20). An acceptable accuracy was predetermined to be P10 = 70% and P20 = 95%. Results The data set included 5158 adults (51.2% women) with sufficient data to calculate all weight estimation methods. The Lorenz method performed best (P10 = 86.8%, P20 = 99.4%) and met the standard of acceptability across sex and body mass index subgroups. The Mercy and PAWPER XL‐MAC methods performed acceptably in non‐obese adults. Conclusion The ideal weight estimation method should be accurate, rapid, simple, and feasible. This study has demonstrated the accuracy of 7 methods. The Lorenz method performed best but is complex and likely to be difficult to apply in resuscitation settings. Other simpler and quicker methods are at least as accurate as the best methods widely used in children, and there is potential for further calibrating these for use in adults before validation in real‐world studies.

Purpose Estimating fetal weight using ultrasound measurements is an essential task in obstetrics departments. Most of the commonly used weight estimation formulas underestimate fetal weight when the actual birthweight exceeds 4000 g. Porter et al. published a specially designed formula in an attempt to improve detection rates for such macrosomic infants. In this study, we question the usefulness of the Porter formula in clinical practice and draw attention to some critical issues concerning the derivation of specialized formulas of this type. Methods A retrospective cohort study was carried out, including 4654 singleton pregnancies with a birthweight ≥ 3500 g, with ultrasound examinations performed within 14 days before delivery. Fetal weight estimations derived using the Porter and Hadlock formulas were compared. Results Of the macrosomic infants, 27.08% were identified by the Hadlock formula, with a false-positive rate of 4.60%. All macrosomic fetuses were detected using the Porter formula, with a false-positive rate of 100%; 99.96% of all weight estimations using the Porter formula fell within a range of 4300 g ± 10%. The Porter formula only provides macrosomic estimates. Conclusions The Porter formula does not succeed in distinguishing macrosomic from normal-weight fetuses. High-risk fetuses with a birthweight ≥ 4500 g in particular are not detected more precisely than with the Hadlock formula. For these reasons, we believe that the Porter formula should not be used in clinical practice. Newly derived weight estimation formulas for macrosomic fetuses must not be based solely on a macrosomic data set.

To test the equivalence of two fetal weight estimation formulas generated by Hadlock, a formula that includes head circumference parameter (H1), and another (H2) which excludes this parameter. A secondary aim was to identify the patients in which H2 formula is less reliable to use.This retrospective cohort study included a total of 1220 sonographic fetal weight estimations performed within seven days of delivery and recorded at a single medical center from January 2014 to December 2016. Estimated fetal weight was calculated using H1 and H2 formulas. Their accuracies were compared using percentage error, the proportion of weight estimations falling within ±15% error interval and by Bland-Altman analysis. Multivariate regression was performed to evaluate factors affecting weight estimation by H2 formula.The mean birth weight was 3288.92 ± 641.27gr. The H2 formula presented with statistically significant higher value of systemic mean percent error comparing to H1 (3.19% vs. 1.87%, p 0.001 respectively). H2 formula had a lower accuracy compared to H1 in predicting fetal weight within ±15% of birth weight (90.49% vs. 93.44%, p 0.01 respectively). Using Bland-Altman analysis, the 95% limits of agreement between both formulas were (-142.03) to 231.79gr with a mean of 44.88gr. Factors found to influence significantly on H2 formula were long femur length (OR 1.144, p 0.0001) and low maternal age (OR 0.947, p 0.01).H1formula was more accurate than H2 formula in predicting fetal weight at term. However, the accuracy difference was found to be small. Therefore, if ultrasonographic evaluation of HC is technically difficult, Hadlock formula that excludes head circumference can be used with confidence. Caution should be paid with higher values of femur length and lower maternal age.

Background Commonly used ultrasound fetal weight estimation formulas show variable degrees of error which is more evident in fetuses with nutritional and metabolic issues; better accuracy of fetal weight estimation can be obtained by incorporation of fetal soft tissue parameters like the fetal subcutaneous tissue in the weight estimation process. The aim of this study was to assess the accuracy of fetal abdominal subcutaneous tissue thickness (FASTT) as an indicator of fetal birth weight. Results FASTT showed a high significant statistical correlation with fetal birth weight (r = 0.94, P value = 0.00); it showed higher sensitivity for large for gestational age (LGA) than small for gestational age (SGA) (90.9% and 86.9%, respectively). The best cutoff value for the detection of LGA was ≥ 9.2 mm and ≤ 4.5 for SGA. FASTT showed lower accuracy than abdominal circumference (AC) as an indicator of LGA (92% versus 96%, respectively). Used alone, FASTT is less sensitive than Hadlock formula in both LGA and SGA (90.9% versus 94.5% in LGA and 86.9% versus 88.9% for SGA, respectively). There was no statistical correlation between FASTT and mode of delivery (r = 0.09, P value = 0.23) nor fetal gender (r = 0.15, P value = 0.11) Conclusion FASTT is a good indicator of fetal birth weight especially LGA, yet it is less sensitive than AC in the prediction of LGA. It cannot be used as a predictor of mode of delivery and not affected by fetal gender.

Background Determination of weight in children is an important aspect of their assessment. It has a wide range of usefulness including assessing their nutritional status and drug dose calculation. Despite its usefulness, weight estimation in children in certain conditions can be challenging particularly in emergency situations or in children who are severely ill or cannot stand on standard scales. The Broselow Tape which is a validated tape that is used to estimate weight based on length was developed using height/weight correlations from Western data. However, considering the variations in anthropometric measurements of children from different geographic locations, there is need to ascertain how accurate it is to estimate weight using the Broselow tape among children in Nigeria. Aim The study was carried out to determine the accuracy in the use of the Broselow Tape in weight estimation among Nigerian children. Method A total 1456 children aged 1–12 years who satisfied the inclusion criteria were enrolled over a 2½ year period from two tertiary health facilities in Enugu state Nigeria. Weight was taken using standard weighing scale and Broselow tape. Data collected was analysed using SPSS. Result Of the 1456 children studied, majority (84.2%) had normal Body-Mass-Index (BMI) while about 4.6% had a low BMI percentile for age. The mean weight difference between the two methods was not significantly different between the 1 to 6 years old category. Significant differences were observed from 7 up to 12 years. The Broselow Tape overestimated weights in 1 year old by 3.88%, 2 years 1.58%, 3 years by 2.13%, 4 years (1.94%) and 5 year (0.07%). After 5 years, the degree of overestimation rises sharply to 4.25% in 6, 9.25% in 7, 7.29% in 8 and 9.29%. 9.18, 11.61% & 6.75% in 9, 10, 11 and 12 years old respectively. The proportion of estimated weights that was within 10- 20% of the actual weight was higher in the 1-6 years age categories compared to weight estimates in older age categories. Conclusion Weight estimates obtained using the Broselow tape correlated better in children that are 6 years or younger compared to those in the older age categories. There is need for re-validation and/or adjustments of the Broselow tape especially in children over 6 years old.

Uganda’s beef industry has been growing slowly and requires sustained monitoring of actors at post-harvest handling points in order to decrease public health risks and losses. This study documented causes of losses and estimated economic values at post-harvest handling points along the beef value chain. It was carried out at slaughter houses, transporters and butcher shops in the districts of Western, Central and Eastern Uganda. A cross sectional study was conducted among meat handlers who were interviewed to find out the losses incurred in the value chain. Microbial load from carcass swabs were collected and evaluated using standard microbiological methods to determine microbial contamination of beef. The causes of losses varied at different handling points. The actors at slaughter houses indicated the major losses were due to low beef demand (15.3%), insecurity (13.4%) and poor weight estimation methods (11.03%). Losses at the butchery included, beef waste (22.4%), drip loss (19.7%) and beef spoilage (18.4%). Microbial analysis showed the highest microbial prevalence at the butchery (70-100%) followed by slaughter (50-80%) and lastly transport (30-50%). Microbial contamination on carcass leads to spoilage and hence market loss because exportation does not admit contaminated foods. Actors reported beef waste and drip loss as the major causes of losses at the butchery. To reduce losses, public health care education for meat handlers and adherence to strict standard operating procedures (SOPs) are a key. Key words: Losses, post-harvest, beef value chain, handling points, Uganda.

Objectives To evaluate different formulas for estimating fetal weight in diabetic pregnancies. Methods This retrospective study evaluated the precision of ultrasound fetal weight estimation in 756 pregnancies complicated by gestational diabetes between 2002 and 2016. The estimated fetal weights (EFWs) were obtained within 7 days of delivery from 10 weight estimation formulas and were compared with pair-wise matched controls from 15,701 patients. The precision of the evaluated formulas for EFW was analyzed by median absolute percentage errors (MAPEs), mean percentage errors (MPEs), and proportions of estimates within 10% of actual birth weight. Results Among the tested formulas, the lowest MAPE was detected with formula I of Hadlock et al (Am J Obstet Gynecol 1985; 151:333-337), and the formula of Schild et al (Ultrasound Obstet Gynecol 2004; 23:30-35) had the highest proportion of estimates within the 10% range. The EFW in diabetic patients showed a slight trend toward overestimation in comparison with the matched controls (MPE estimates showed a trend toward more positive values). In most of the EFW formulas that were evaluated, no significant differences were detected in MAPEs and estimates within the 10% range. The MPE estimates with most formulas in both groups were close to zero. Overall, the differences between most of the evaluated formulas were small. Conclusions Little evidence was found for differences in the accuracy of the EFW in diabetic pregnancies and controls. The Hadlock I formula showed the lowest MAPE, and the Schild formula had the highest proportion of estimates within the 10% range.

Stroke is a clinical emergency requiring urgent recombinant tissue-type plasminogen activator treatment in eligible patients. The dosage of thrombolytic agent (alteplase) is weight dependent. However, many patients receive thrombolytic therapy based on weight estimation. Here, we assess the frequency of incorrect thrombolytic therapy dose as a result of weight estimation and evaluate the short-term safety and efficacy of alteplase misdose. Of 237 patients, weight was estimated in 147 (62%), of which 33 patients (22.4%) were treated with an erroneous dose of alteplase. An incorrect dose was associated with neither poor outcome nor a lower risk of hemorrhage. We conclude that hospitals should implement reliable methods for measuring patients' weight that could be easily applied and would not cause delays to the treatment of stroke patients.

OBJECTIVES: To determine the accuracy of using parental estimate of a child's weight compared to actual weight in a paediatric emergency setting. METHODS: Prospective, observational study. Age, weight and height data were collected from children aged 1 month up to 11 years with an Australian Triage score of 3 or higher. This was compared with a parent weight estimate. Analysis is descriptive. RESULTS: A total of 450 children were studied with a mean age of 4 years 4 months. A total of 85.3% of parents were willing to provide a weight estimate (n = 384). The mean difference between the parent estimate (where provided) and the actual weight was 0.33 kg (measured weight > estimated; 95% confidence interval [CI] -6.9 kg to +7.6 kg). There was 75% agreement within 10% of the measured weight (95% CI 71-79%) and 92% agreement within 20% of the measured weight (95% CI 89-95%). Weight was more commonly underestimated than overestimated. Children of Polynesian/Pacific ethnicity were less likely to have an accurate parental weight estimation. CONCLUSIONS: Parent estimate is an accurate weight estimation method when parents are willing to give an estimate. There is ethnic variation in accuracy that should be taken into account when applying this method.

Objective: Ultrasound estimation of foetal weight is a very important aspect of antenatal care. The role of amniotic fluid volume as a potential factor which may impede the relevance of ultrasonographic foetal weight estimation is still questionable. The aim of our study was to evaluate the impact of isolated oligohydramnios on the accuracy of ultrasound foetal weight estimation in at term pregnancies when examination was performed within 48 h before delivery. Materials and methods: The retrospective cohort study included 1831 women with low-risk, singleton, at term pregnancy. Estimated foetal weight (EFW) was calculated using Hadlock-4 formula. Exclusion criteria consisted of multiple pregnancies, active phase of labour, preeclampsia, foetal growth restriction, foetal anomalies, gestational diabetes mellitus and the evidence of intrauterine infection. Isolated oligohydramnios was defined as Amniotic Fluid Index (AFI) ≤50 mm without any other foetal anomalies. EFW and actual birth weight (ABW) were compared by calculation of: absolute error (AE), absolute percentage error (APE) and substantial error (SE) = APE >10%. Results: Participants were divided into 2 groups: Group 1: patients with normal AFI (50 ≤ AFI ≤250 mm; n = 1602) and Group 2: (isolated oligohydramnios, n = 229). There were not observed statistically significant differences between mean ABW and mean EFW in both groups (Group 1: p = 0.525; Group 2: p = 0.317). Mean AE in Group 1 was 221.8 g and 223.1 g in Group 2 (p = 0.919). Mean APE was 6.54% and 6.64% in Group 1 and 2 respectively (p = 0.816). SE ratio was 21.9% in Group 1 and 19.2% in Group 2. Underestimation to overestimation ratio in Group 1 was 1.01 and 0.84 in Group 2. Conclusions: Amniotic fluid volume has limited impact on ultrasound foetal weight estimation. In oligohydramnios group there might be a tendency of overestimation of neonatal ABW. Keywords: Estimated foetal weight, Amniotic fluid index, Ultrasound examination, AFI, EFW

Accurate weight estimation is important for calculating appropriate medication dosages, determining rates of fluid replacement, and selecting correct equipment sizes in critically ill children requiring resuscitation. The actual measurement of the weight of a critically ill or injured child is often not possible. The Broselow Pediatric Emergency Tape (BT) is an important tool for predicting a child's weight based on his/her height. Although BT has previously been validated, given the increasing prevalence of obesity in today's society, it behooves clinicians relying on this resuscitation aid to revisit the issue.The aim of this study was to evaluate the accuracy of the color-coded BT in weight estimation and the influence of obesity on its accuracy.This is a retrospective study conducted in a pediatric clinic of urban hospital. This study reviewed the medical records of children up to 96 months of age, who presented during 2008-2010. We recorded the child's age (in months), actual (measured) weight (in kilograms), and height (in centimeters). Based on the height, weight estimation was obtained using the color-coded BT. The actual weight was compared with the predicted weight obtained by the height-based BT. Patients presenting with any medical condition that would substantially affect growth of the child were excluded. A univariate logistic regression model was utilized to predict any underestimation based on age, sex, and body mass index (BMI) percentile.The medical records of 538 children were reviewed. There was a discrepancy in 226 children (42%). Broselow Pediatric Emergency Tape underestimated weight (measured weight was higher than predicted weight) in 158 children (29.4%) and overestimated (measured weight was lower than predicted weight) in 68 children (12.6%). Of the 158 underestimated children, 138 were off by 1 color zone, 16 by 2 color zones, and 4 by more than 2 color zones. When characterized by BMI, 46 children (13.6%) had normal BMI, 27 (45.8%) were overweight, and 84 (80.8%) were obese, whereas one child (2.8%) was underweight.In our population, BT was inaccurate in predicting weight in 42% of children (underestimation in 158 children [29.4%] and overestimation weight in 68 children [12.6%]). However, the majority of discrepancies involved only 1 BT color zone. Emergency physicians should be aware of this discrepancy until more accurate methods become available.

Background: One of the most important parameters that must be obtained when resuscitating a critically ill or injured paediatric patient is their weight. The best known paediatric weight estimation system is arguably the Broselow Tape, but the tape has been shown to be very inaccurate. The aim of this study was to determine and compare the accuracy of the Broselow tape, a modified Broselow tape system, the PAWPER XL tape and the hanging leg weight technique for potential utilisation in the paediatric resuscitation setting. Methods: A convenience sample of 200 children between the ages of 1 month and 16 years were enrolled. All the children’s weights were estimated using the Broselow tape, a habitus-modified Broselow tape system, the PAWPER XL tape and the hanging leg weight technique. Overall accuracy was evaluated using the percentage of weight estimations falling within 10% of actual weight (PW10). Results: The PAWPER XL tape performed the best, whilst the hanging leg weight technique performed the poorest with PW10s of 74% and 19.5%, respectively. The Broselow tape with and without habitus-modification only showed modest accuracy, with PW10s of 61.7% and 59.1% respectively. Conclusions: The PAWPER XL tape performed significantly better than other weight estimation systems and is most appropriate for use in South African paediatric emergencies. The habitus-modified Broselow system produced only modest improvement in overall weight estimation accuracy of the Broselow tape.

Introduction The Broselow tape (BT) is a useful pediatric tool for weight estimation and dosing reference during emergency care. Many accuracy studies have been performed for various countries and regions of the world but there is very little information for Latin American countries. The primary objective of the study was to assess the accuracy of the BT in a Peruvian pediatric population. Methods This was a retrospective cross-sectional study of 1,160 children aged two to 19 years from three outpatient clinics in La Libertad, Lima, and Iquitos, Peru. Patient height and weight were measured and compared with the weight and color zone generated by the 2017 edition of the BT. Accuracy was estimated by statistical comparison of mean absolute percent differences, error within 10% (EW10), and color zone agreement. Results Comparison of mean differences between measured weight (MW) and estimated BT weight shows that the BT underestimates actual weight for all color zones in this population. Likewise, the Bland-Altman plot of agreement between estimated and measured weights shows an overall underestimation, or bias, equal to 1.60 kg. The overall percent difference was -7.84% with differences gradually increasing for weights over 10 kg. In terms of accuracy, the overall error within 10% was 62.8%. Conclusion The BT underestimates the actual weight of Peruvian pediatric patients in all color categories, particularly in children with higher body mass indexes. Underestimation of weight may lead to the use of non-therapeutic medication doses or incorrect equipment sizes and, subsequently, ineffective resuscitation.

In a broiler carcass production conveyor system, inspection, monitoring, and grading carcass and cuts based on computer vision techniques are challenging due to cuts segmentation and ambient light conditions issues. This study presents a depth image-based broiler carcass weight prediction system. An Active Shape Model was developed to segment the carcass into 4 cuts (drumsticks, breasts, wings, and head and neck). Five regression models were developed based on the image features for each weight estimation (carcass and its cuts). The Bayesian-ANN model outperformed all other regression models at 0.9981 R2 and 0.9847 R2 in the whole carcass and head and neck weight estimation. The RBF-SVR model surpassed all the other drumstick, breast, and wings weight prediction models at 0.9129 R2, 0.9352 R2, and 0.9896 R2, respectively. This proposed technique can be applied as a nondestructive, nonintrusive, and accurate on-line broiler carcass production system in the automation of chicken carcass and cuts weight estimation.

An optimal model to evaluate the weight of the whole body of Asian sea bass with and without fins was generated using computer vision image processing techniques. Image data of 25 fish randomly selected were collected every week for one month. The data were divided into two sets by means of a 40 - 60 % split-test, 40 % (10 fish; 100 images) were used as training data and 60 % (15 fish; 150 images) were used as out-samples or validation data. The model using fish images without fins gave a higher average and total coefficient of determination (N150R2 = 0.77 ± 0.10, N600R2 = 0.96) than using images with fins (N150R2 = 0.24 ± 0.20, N600R2 0.63). Errors as root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE), maximum absolute error (MXAE), and maximum relative error (MXRE) were compared using mathematical models. Results showed that the model using fish images without fins recorded fewer errors, with average values of 9.19 ± 3.74 g, 6.06 ± 3.64 g, 5.18 ± 3.08 %, 8.87 ± 3.26 g and 0.12 ± 0.12 %, respectively compared with fish images with fins at 12.35 ± 4.45 g, 11.26 ± 3.61 g, 9.69 ± 2.94 %, 11.50 ± 4.71 g and 0.14 ± 0.11 %, respectively. Comparison between models, with and without fins, and normal manual measurement methods found no statistically significant differences (P > 0.05). Therefore, this technique may be applied for weight estimation in real pond conditions to give advantages of reduced time, stress and injury, with minimal interference in fish feeding compared to physical capture and weighing. HIGHLIGHTS 2D Computer vision techniques can be applied for fish weight estimation Fish images without fins show better results than those of with fins The advantages of this technique are reduced time, stress and injury compared to physical capture and weighing Step toward development of an automatic fish weight monitoring when the fish is swimming freely in the water GRAPHICAL ABSTRACT

The appearance, size, and weight of poultry meat and eggs are essential for production economics and vital in the poultry sector. These external characteristics influence their market price and consumers' preference and choice. With technological developments, there is an increase in the application and importance of vision systems in the agricultural sector. Computer vision has become a promising tool in the real-time automation of poultry weighing and processing systems. Owing to its noninvasive and nonintrusive nature and its capacity to present a wide range of information, computer vision systems can be applied in the size, mass, volume determination, and sorting and grading of poultry products. This review article gives a detailed summary of the current advances in measuring poultry products' external characteristics based on computer vision systems. An overview of computer vision systems is discussed and summarized. A comprehensive presentation of the application of computer vision-based systems for assessing poultry meat and eggs was provided, that is, weight and volume estimation, sorting, and classification. Finally, the challenges and potential future trends in size, weight, and volume estimation of poultry products are reported.

Background MM is a hematological malignancy always evolving from pre-malignant stages, with progressive increase of genomic complexity. MM is characterized by a large abundance of copy number alterations (CNA); many of them, regarded as “driver”, stack up progressively from early tumor stages, causing biological changes that give rise to tumor hallmarks and malignant phenotypes. The combined application of whole genome analysis and mathematical models allows to deeply describe these alterations and to infer their order of acquisition during oncogenesis from their clonality levels, assuming that clonal ones are more ancestral than subclonal. Aims: (1) To define the temporal order of acquisition of CNA, leading to the onset of symptomatic MM and (2) to define a scoring model able to stratify patients (pts) according to the ancestrality of the alterations observed in their genomic landscape. Methods Genomic data collected from a total of 1384 newly diagnosed MM pts were included in the study: SNPs array data were collected from 514 pts of our Institution (BO dataset); in 870 pts, WES data were downloaded from CoMMpass study. CN calls and clonality levels were harmonized by an analysis pipeline including ASCAT, GISTIC v2 and custom R scripts. Timing estimates were obtained with BradleyTerry2 package. Survival analysis were performed on R. Results A full call-set of CNAs was obtained by harmonizing BO and CoMMpass datasets. The clonality information was first extrapolated from the whole call-set, to define the temporal order of acquisition of non-primary CNAs. CNAs were then accurately ranked, by using the obtained timing estimates, characterized by a quite narrow confidence interval. Of interest, chr 1q gains and chr 13q losses were frequently clonal and ranked as ancestral events, whereas chr 17p losses were late occurring events. By weighting the CNAs carried by any given pts at diagnosis with their relative timing estimate in a combinatorial process, an Ancestrality Index (AI) was defined for each pts (median AI=3.4, IQR=1.7-6.0). The AI was found to be significantly associated with progression free (PFS) and overall survival (OS) (p3.4 (i.e. with a more “ancestral” profile) had a worse outcome as compared to the rest of pts (OS 40% vs 58%, PFS 42% vs 56%, at a median follow up of 92m and 34m, p Conclusions By means of whole genome analysis and dataset harmonizing, the temporal order of acquisition of MM CNAs has been confidently described. A score reflecting the disease ancestrality of MM pts at diagnosis was generated and associated to survival outcomes. Overall, these findings support the evidence that MM pts at diagnosis carrying an excess of ancestral alterations, expected to likely be drivers, are prone to have a dismal prognosis.

Introduction:The aim of this study was to investigate the usability of the age value listed on the labels on children’s clothes in the age-based weight estimation method recommended by the Pediatric Advanced Life Support (PALS) guidelines.Material-Method:This prospective, cross-sectional study was organized in Antalya Training and Research Hospital Emergency Department. Children aged between 1-12 years were included in the study. The weight measurements of the children were obtained based on the age-related criteria on the labels of their clothes. The estimated values were compared with the real values of the cases measured on the scale.Results:One-thousand ninety-four cases were included, the mean age of cases in age-based measurements was 6.25 years, which was 6.5 years in label-based measurements. Average weights measured 25.75kg according to age-based measurements, 26.5kg according to label-based measurements, and 26.0kg on the scales, and showed no statistical difference (P Conclusion:In the emergency department and prehospital setting, children with an unknown age and that need resuscitation and interventional procedures for stabilization, and have no time for weight estimation, checking the age on clothing label (ACL) instead of the actual age (AA) can be safely used for the age-dependent weight calculation formula recommended by the PALS guide.

Background. The weight of a patient is an important variable that impacts on their medical care. Although some drugs are prescribed on a so-called ‘adult dose’ basis, we know that adults come in all shapes and sizes – a ‘one- dose -fits-all’ approach is not necessarily appropriate. As a measured weight may not always be available, an alternative method of accurately estimating weight is required. Objectives. To assess and compare the accuracy of weight estimations in adults by patient self-estimation, the Mercy method, Buckley method, Broca index and PAWPER XL-MAC (paediatric advanced weight prediction in the emergency room eXtra length/eXtra large mid-arm circumference) method. Methods. This was a prospective, cross-sectional study conducted at a tertiary academic hospital in a metropolitan area of Johannesburg, South Africa. Anthropometric variables of height, abdominal circumference, thigh circumference, mid-arm circumference and humeral length were measured. These variables were then applied to the various weight estimation methods and compared with the patient’s actual weight. Results. There were 188 adult patients included in the study. None of the methodologies evaluated in this study achieved the recommended >70% of weight estimations within 10% of the patient’s actual weight (PW10). The Mercy method was the closest to achieving greater than the recommended 95% for weight estimation falling within 20% of the patient’s actual weight (PW20). The PW20 for the Mercy method was 91.5%. The PAWPER XL-MAC and patient self-estimate methods achieved a PW20 of 85.1% and 86.1%, respectively. The Broca and Buckley methods performed poorly overall. Conclusions. None of the evaluated weight estimation methodologies was accurate enough for use in adult weight estimation. The Mercy and PAWPER XL-MAC methodologies both showed significant promise for use in adult weight estimation, but need further refinement. Although patient self-estimates were similarly accurate to those found in previous studies, they were not an accurate option; self-estimations would remain the first choice if the patient was able to provide such an estimation. The Broca index and Buckley method cannot be recommended owing to their poor performance.

The development of so-called soft-biometrics aims at providing information related to the physical and behavioural characteristics of a person. This paper focuses on body weight estimation based on the observation from a top-view RGB-D camera. In fact, the capability to estimate the weight of a person can be of help in many different applications, from health-related scenarios, to business intelligence and retail analytics. To deal with this issue, a TVWE (Top-View Weight Estimation) framework is proposed with the aim of predicting the weight. The approach relies on the adoption of Deep Neural Networks (DNNs) that have been trained on depth data. Each network has also been modified in their top section to replace classification with prediction inference. The performance of five state-of-art DNNs have been compared, namely VGG16, ResNet, Inception, DenseNet and Efficient-Net. In addition, a convolutional auto-encoder has also been included for completeness. Considering the limited literature in this domain, the TVWE framework has been evaluated on a new publicly available dataset: “VRAI Weight estimation Dataset”, which also collects, for each subject, labels related to weight, gender, and height. The experimental results have demonstrated that the proposed methods are suitable for this task, bringing different and significant insights for the application of the solution in different domains.

Commercial aircraft have well-designed and optimized systems, the result of a huge experience in the field, due to the large fleet of aircraft in operation. For light, utility, or sports aircraft, with a multitude of shapes, tasks, and construction types, there are different solutions that seek to best meet the requirements of the designed aircraft. In this sense, for a sport plane, an increased maneuverability is desired, and the system that controls flaps and wing must be properly designed. A new flap mechanism command solution is proposed and justified in the paper, for use in sports and recreational aviation, in order to achieve angles of braking greater than 40°, take-off and landing in a shorter time and over a shorter distance, as well as the gliding of the aircraft in critical flight conditions or when fuel economy is needed. A finite element model is used to verify the optimized command system for the flap and wing and to check if the strength structure of the aircraft is properly designed. The main result consists of the new design command system for flaps and wings and in verifying, by calculation, the acceptability of the new mechanism proposed from the point of view of the strength of the materials.

Future frame prediction in videos is a challenging problem because videos include complicated movements and large appearance changes. Learning-based future frame prediction approaches have been proposed in kinds of literature. A common limitation of the existing learning-based approaches is a mismatch of training data and test data. In the future frame prediction task, we can obtain the ground truth data by just waiting for a few frames. It means we can update the prediction model online in the test phase. Then, we propose an adaptive update framework for the future frame prediction task. The proposed adaptive updating framework consists of a pre-trained prediction network, a continuous-updating prediction network, and a weight estimation network. We also show that our pre-trained prediction model achieves comparable performance to the existing state-of-the-art approaches. We demonstrate that our approach outperforms existing methods especially for dynamically changing scenes.

Many algorithms now exist for discovering process models from event logs. These models usually describe a control flow and are intended for use by people in analysing and improving real-world organizational processes. The relative likelihood of choices made while following a process (i.e., its stochastic behaviour) is highly relevant information which few existing algorithms make available in their automatically discovered models. This can be addressed by automatically discovered stochastic process models.

Background International guidelines have promoted the use of length-based tapes for emergency weight estimation in children. This is primarily because of a perception that more modern methods might require more training than can practically be achieved. This study aimed to evaluate the inter-rater reliability of novice users of the PAWPER XL (paediatric advanced weight-prediction in the emergency room) tape as an indicator of the ability to use the device effectively with limited training. Methods This was a secondary analysis of unpublished data from three previous studies. Inter-rater reliability analyses were performed for each study for the accuracy of weight estimations and for the assignment of body habitus score. Inter-rater reliability was analysed using percentage agreement and Cohen's Kappa for Study 1 and intraclass correlation (ICC) for Study 2 and Study 3. A value of

An improved method was proposed to estimate the structural ratios of a multistage liquid rocket for the early design stages, for example, the preliminary sizing analysis, or mission design ...

A significant application has been found in making the task of automation easier. Computer vision is a very powerful method for understanding the contents from the images. Weighing sheep for the analysis of their health and growth is a very arduous task, and traditional methods of weighing using a balance are very time-consuming. Estimating sheep weights using computer vision algorithms has already been tried, but these methods are not efficient enough. They also require some extra instruments set-up. We tried to utilize this powerful technology to make the difficult task of estimating sheep weights quick and accurate. We bring a novel approach to image segmentation in order to calculate the area of the sheep directly. The various other features are fed to a neural network-based regression model for achieving better results for the task of estimating sheep’s weight. The proposed approach has enabled us to minimize the complexities of carrying heavy equipment and errors through human involvement in measuring the weight of the sheep.

BackgroundIn obese children, lipophilic medications should be dosed to total body weight (TBW) and hydrophilic medications to ideal body weight (IBW). During emergencies these weights need to be estimated to ensure that urgent drug therapy is accurate and safe. The Mercy method is a well-established weight estimation system that has recently been adapted to provide estimations of body length in children. It was therefore conceivable that this could be further modified to provide estimations of IBW.MethodsA model was developed a priori using the Mercy method’s humeral length segments to predict IBW. The accuracy of this model was then tested in a sample of 13134 children from the National Health and Nutrition Examination Survey (NHANES) datasets. The accuracy of IBW estimation was determined from the percentage of estimations falling within 10% (p10) and 20% (p20) of true IBW. The model was also tested to see the accuracy of detection of obesity in the study sample.ResultsFrom the sample of 13134 children, a subset of 1318 obese children were identified. In this subset, the new Mercy method model achieved an IBW estimation accuracy p10 of 66.9% and a p20 of 95.1%. For the detection of the obese child, the model had a sensitivity of 88.6% and a specificity of 75.8%.ConclusionsThis study established that the Mercy method can be modified to provide a reasonably accurate estimation of IBW in obese children, with very few critical errors. The ability to the model to identify the obese child was also reasonably accurate, on a par with other such predictive methods. While other accurate methods of estimating both TBW and IBW exist, such as the PAWPER XL tape, the modified Mercy method is an acceptable alternative if such other devices are not available.